The purpose of this grant is to transform the way we approach studying complex phenotypes in mammalian cell culture by innovating new ways to screen for such phenotypes using a comprehensive set of barcoded cell lines. In vitro propagated lines derived from normal and transformed human tissues have provided an important model for studying cell biology and gene function. While forward genetic screening has been a powerful approach to understand the genetic underpinnings of various phenotypes, variability at the epigenetic level, and complex genetic variability cannot easily be modeled by forward genetics. In contrast, the variability between cell lines produces complex phenotypes that mimic biologically relevant states, such as chemotherapeutic resistance. Comprehensive projects, such as the Broad/Novartis Cancer Cell Line Encyclopedia (CCLE), have been devoted to providing genome sequencing, gene expression, and copy number data for over 1,000 cell lines. While these data have facilitated the identification of cell lines with desired genetic alterations or gene expression patterns, the measurement of complex phenotypes across large panels of cell lines remains a labor intensive and expensive task. To address this problem, we devised a lentiviral-based strategy to deliver DNA barcodes to individual cell lines, allowing us to follow their abundance in a cell competition assay. This technique allowed us to accurately and simultaneously measure the low glucose sensitivity of a panel of 28 suspension cell lines. Here, we propose implementing cell barcoding based assays to simultaneously determine how hundreds of cell lines respond to any desired stimulus. We will produce a set of 200 barcoded cell lines and test our ability to measure the sensitivity of these cell lines to low glucose in established assays. We will then expand the set of validated environmental and genetic perturbations that can be screened, including expression of specific cDNAs, shRNAs, sgRNAs, drug treatment, and environmental perturbations. Moreover, we will evaluate our ability to perform these experiments in soft agar, basement membrane matrix, or as tumor xenografts. Finally, we will develop a Fluoresce-Activated Cell Sorting (FACS) based assay for pooled high-throughput analysis of fluorescent markers and reporters. This approach will greatly expand the number of outputs which can be used with this technology, including immunofluorescence of native or modified proteins and fluorescent reporters. To evaluate this technology, we will use FACS based approaches to identify cell lines that are responsive or non- responsive to mTOR pathway modulation following amino acid starvation and re-stimulation and determine whether this phenotype can be predicted by mutations in the mTOR pathway. If successful, the technology enabled by this grant will allow a starting lab to ask questions similar to those typically posed by major consortium efforts.

Public Health Relevance

Here we propose to develop a method for simultaneously studying the response of a large panel of human derived cancer cells to various perturbations (e.g. chemotherapeutic treatment). By innovating both the number of cell lines that can be evaluated at once and the types of perturbation that can be studied in this format, we will be have a greater ability to determine why cancer cells respond in this way, and therefore the power to predict how cancer cells from other patients will respond. Furthermore, this technology will allow such experiments to be conducted more rapidly and at a lower cost than current methods.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21CA198543-02
Application #
9098652
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Kuhn, Nastaran Z
Project Start
2015-07-01
Project End
2017-06-30
Budget Start
2016-07-01
Budget End
2017-06-30
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
New York University
Department
Pathology
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016
Minton, Denise R; Nam, Minwoo; McLaughlin, Daniel J et al. (2018) Serine Catabolism by SHMT2 Is Required for Proper Mitochondrial Translation Initiation and Maintenance of Formylmethionyl-tRNAs. Mol Cell 69:610-621.e5
Garcia-Bermudez, Javier; Baudrier, Lou; La, Konnor et al. (2018) Aspartate is a limiting metabolite for cancer cell proliferation under hypoxia and in tumours. Nat Cell Biol 20:775-781